What’s Up @ Kno.e.sis?Review of Sheth’s Group

(Updated Dec 2015)

Sheth Group: All Funded

Our Group’s Research Themes (2014)

Vision: Computing for Human Experience.

Strategy: Innovation with real-world impact.

Themes:

• Big Data/Smart Data

• Physical-Cyber Social Computing

• Semantic Web

• Semantic Social Web and Computational Social Science Semantic

Sensor Web (IoT/Web of Things)

• Personalized Digital Health

• Health Informatics, Crisis Informatics

See: http://knoesis.org/vision

A Unique approach

Aspects Shared by Our Projects: • Real-world impact through partnership/collaboration with domain

scientists/end-users.

• Often addresses important human/social/economic development

challenges.

• Real-world scale: at minimum, developing robust prototypes (open

source tools/platforms) using real-world data and knowledge; often

pursues multidisciplinary research.

• Tendency to lead to operational applications/tools/systems,

technology transfer, products, or services.

• High-risk/high-impact; avoids incremental work.

Sample Questions Driving Our Research

• Can we predict health changes/deterioration (e.g., asthma attacks) for intervention

before an episode occurs in order to prevent them altogether?

• Can we make computers recognize implicit information present in medical records in

order to provide a comprehensive data set to the models that attempt to understand

patient health status?

• Can we automatically extract highly sparse actionable intent of emerging resource

needs and availability, as well as match them during dynamic disaster response,

which aids situational awareness & coordination?

• Can we mine societal beliefs, lack of services, and laws from social media

conversations on gender-based violence to assist regional policy makers?

• Can we empower city authorities to make policy decisions by predicting impending

city issues such as traffic, crime, and pollution?

Student Success: Our most important performance measure

Exceptional publication impact: 11 out of Sheth’s 20 PhDs have 1,000+

citations each (3 over 5,000);

Average citation for Sheth’s first 18 PhDs: 1,400+

Publications in top venues and conferences:

• ACM TIST, VLDB Journal, Comp in Human Behavior, AAAI,

CSCW Journal, Web Semantics JMIR, JBI, First Monday

• ACL, ICWSM, CSCW, ISWC, SocInfo, ESWC, VLDB, WWW, AMIA

Serving on top conference PCs: WWW, ISWC, ESWC, CIKM, ICWSM,…

Major Awards: 2015-2016 George Thomas Post-Graduate Fellowship,

2015 Eric & Wendy Schmidt Data Science for Social Good Fellowship,

2015 USAID and ICT4Peace Fellowship,

2014 ITU Telecom World Young Innovators, etc.

Outstanding or Best CS Department student award: all years since 2007

Student Success: continued

Exceptional first jobs Tenure track/tenured at higher ranked departments, e.g., George Mason U., Case

Western Reserve University, North Carolina State University

Top research labs/high-tech companies: IBM Almaden Research, IBM TJWatson

Research, Amazon, CISCO

Successful entrepreneurs

Exceptional starting salaries: six figures for M.S.

Exceptional internships: IBM Research Almaden/Watson, HP Research, Samsung

Research, Bosch R&D, Mayo, NLM, PNNL, etc.

Exceptional professional services: Invited talks; PC membership of 10-20

conferences, usually involving top conferences in their fields

50% of the Sheth’s PhDs have filed at least 2 patents; 1 former PhD has filed

30+ patents.

Showcase

Showcase: http://knoesis.org/hemant

Showcase: http://knoesis.org/researchers/cory

We are well funded:

Projects with Sheth as a PI > 7.6 million

Total Kno.e.sis active funds > 8.3 million*

* Only funds where a Kno.e.sis faculty is PI or joint PI are counted (funds

with faculty as co-PI or investigator are not counted)

CityPulse: Smart Data for Smart Cities

Physical-Cyber-Social computing for SmartCity:

Semantic integration of and reasoning over IoT/sensor and social big

data to power advanced smart city applications.

Sponsor: EU City Pulse Consortium

CityPulse: Synergistic Social/Sensor/IoT

Streaming Data Analysis

City Traffic Event Extraction from Twitter Stream

Active (green) and Scheduled (yellow)

Events in San Francisco Bay Area

Heatmap of events in Bay Area

What are the events that influence traffic in a city?

What is the impact of these events on traffic delays?

Twitris

Most comprehensive, commercial grade real-time semantic

analysis of social

Media combined with domain-specific and domain

independent background knowledge and open data.

Provides campaigns that anyone can run for deep insights

and actionable information from big social and Web data.

Components used in major crisis such as JK Floods 2014,

Chennai Floods 2015, etc. [see media coverage]

Funded by: NSF SOCS, AFRL, NSF I-CORPS, NSF PF:AIR-TT

Dimensions of Analysis

More on this

SOCS: Social Media Based Coordination

During Disasters

During the Jammu-Kashmir flood, digital volunteers used Twitris technology and

SOCS research to identify rescue requests, to redirect the Indian Army’s rescue

team, and to identify key influencers to increase public outreach.

SOCS team provided a massive (32,000+ messages) Twitter stream and its

filtering analysis via a web interface for a regional emergency preparedness

functional exercise involving public information officers (PIOs) of hospitals, fire

departments, and the local Red Cross, as well as city and county government

officials.

It is a service to mine request-offer intentions for help, and it has been open

sourced and integrated with Ushahidi’s CrisisNET - the firehose of crisis data.

http://knoesis.org/amit/media

Sponsor: NSF

SOCS: Social Media Based Coordination

During DisastersKey technical advancements:

• Technology to identify and match intent from user-generated content (UGC)

using knowledge of psycholinguistic-patterns in the classification.

• Target-specific sentiment analysis to improve semantic understanding of UGC

by leveraging domain-specific vocabularies.

• Defining a novel method of understanding group dynamics via divergence in

group discussions over time, which merges content analysis with traditional

approach of networks, employing socio-psychological theories.

• Efficient community discovery using content and networks (OSU team).

Project: http://knoesis.org/projects/socs

Real-time matching of supply

with needs during a disaster

First Monday paper

PREDOSE: PREscription Drug abuse Online

Surveillance and Epidemiology

A social media analytics semantic web platform developed to

detect emerging patterns and trends in prescription drug abuse

through automatic information extraction from unstructured text.

Funded the same week the White House announced its

initiative to curb prescription drug abuse.

Project: http://wiki.knoesis.org/index.php/PREDOSE

Partner: Center for Interventions, Treatment and Addictions Research (CITAR)

PREDOSE: Purpose

To determine user knowledge,

attitude, and behavior related to

the non-medical use of

pharmaceutical opioids (namel

buprenorphine) as discussed on

Web forums.

To determine spatio-temporal

thematic patterns and trends in

pharmaceutical opioid abuse as

discussed on Web forums.

PREDOSE: Key Technical Issues

Use of structured background knowledge to enhance:

• Entity identification and disambiguation

• Relationship extraction

• Triple Extraction

• Sentiment Analysis

• Template Patterns

• Trend Analysis

PREDOSE: Key Outcomes

• Loperamide discovery; drug users abuse imodium for self

medication from withdrawal by megadosing. Clinical side effect

(PMVT). Reported finding led to a warning to users, issued on one

of the selected sites for the study.

• Knowledge-aware search; a hybrid approach to information retrieval

using a context free grammar (CFG) to interpret data from four

diverse categories (ontology, lexicon, lexico-ontology, rules)

kHealth

With the increasing number of affordable sensors and computing

power, it is now possible to address a large number of healthcare

challenges that can have profound implications using dHealth,

mHealth, and AI technologies.

Our specific interest is in the early indicators of health change.

kHealth

kHealth

Key Research & Technology:

• Knowledge Representation to describe a domain (logic

and probabilistic).

• Semantic Perception to derive abstractions from raw

data.

• Efficient execution on resource constrained devices.

kHealth

Current kHealth applications:

• Reducing re-hospitalization of ADFH patients

• Reducing asthma incidences in children*

• Improving patient care and caregiver support for

patients with dementia*

• Reducing rehospitalization of GI patients

* On-going testing and evaluation with patients under clinical care under approved IRB

Video: http://youtu.be/mATRAQ90wio

eDrug Trends

Ohio Center of Excellence in Knowledge-Enabled Computing

Principal Investigators: Prof. Amit P. Sheth, Prof. Raminta Daniulaityte

Co-Investigators: Robert Carlson, Krishnaprasad Thirunarayan, Ramzi Nahhas,

Silvia Martins (Columbia), Edward W. Boyer (U. Mass.)

PhD Students: Farahnaz Golroo, Sanjaya Wijeratne, Lu Chen, Adarsh Alex

MS Student: Adarsh Alex

Postdoctoral Researcher: Francois Lamy

Software Engineer: Gary Smith

NIH Award#: 5 R01 DA039454-02

Trending: Social media analysis to monitor cannabis and synthetic

cannabinoid use

Timeline: 15 Sep. 2014 - 14 Sep. 2018

Award Amount: $1,689,019 + $162,505

eDrugTrends

Key questions addressed in eDrugTrends:

• How to identify and compare trends in knowledge, attitudes, and

behaviors related to cannabis and synthetic cannabinoid use

across U.S. regions with different cannabis legalization policies

using Twitter and Web forum data.

• How to identify key influencers (opinion leaders) in cannabis and

synthetic cannabinoid-related discussions on social media.

Partner: Center for Interventions, Treatment and

Addictions Research (CITAR)

Context-Aware Harassment

Detection on Social MediaPrincipal Investigators: Prof. Amit P. Sheth

Co-Investigators: Valerie Shalin, Krishnaprasad Thirunarayan

Other Faculty: Debra Steele-Johnson, Dr. Jack L. Dustin

PhD Students: Lu Chen, Wenbo Wang, Monireh Ebrahimi, Kathleen Renee Wylds

MS Students: Pranav Karan, Rajeshwari Kandakatla

Collaboration with Beavercreek High School

Ohio Center of Excellence in Knowledge-Enabled Computing

NSF Award#: CNS 1513721

TWC SBE: Medium: Context-Aware Harassment Detection on Social Media

Timeline: 01 Sep. 2015 - 31 Aug. 2018

Award Amount: $925,104 + $16,000 (REU)

Social and Physical Sensing Enabled Decision Support for

Disaster Management and Response

Principal Investigators: Prof. Amit P. Sheth, Prof. Srinivasan Parthasarathy (OSU)

Co-Principal Investigators: Densheng Liu (OSU), Ethan Kubatko (OSU), Valerie Shalin,

Krishnaprasad Thirunarayan

PhD Students: Sarasi Lalithsena, Pavan Kapanipathi, Hussein Olimat

MS Student: Siva Kumar

Postdoctoral Researcher: Tanvi Banerjee

Ohio Center of Excellence in Knowledge-Enabled Computing

NSF Award#: EAR 1520870

Hazards SEES: Social and Physical Sensing Enabled Decision Support for

Disaster Management and Response

Timeline: 01 Jul. 2015 - 31 Jul. 2019

Award Amount: $1,975,000 (WSU: $787,500)

Modeling Social Behavior for

Healthcare Utilization in DepressionPrincipal Investigators: Prof. Amit P. Sheth, Prof. Jyotishman Pathak (Cornell)

Co-Investigators: Krishnaprasad Thirunarayan, Tanvi Banerjee, William V. Bobo (Mayo Clinic),

Nilay D Shah (Mayo Clinic), Lila J Rutten (Mayo Clinic), Jennifer B McCormick (Mayo Clinic),

Gyorgy Simon (Mayo Clinic)

Other Faculty: Debra Steele-Johnson, Jack Dustin

PhD Students: Ashutosh Jadhav, Amir Hossein Yazdavar, Hussein Al-Olimat

Master Student: Surendra Marupudi

Visiting Scholar: SoonJye Kho

Ohio Center of Excellence in Knowledge-Enabled Computing

NIH Award#: 1 R01 MH105384-01A1

Modeling Social Behavior for Healthcare Utilization in Depression

Timeline: 1 Jul. 2015 - 30 Jun. 2019

Award Amount: $1,934,525 (WSU: $505,600)

Additional Funded Projects (incomplete list)

● PFI: AIR-TT: Market-driven Innovations and Scaling up of Twitris - A System for Collective

Social Intelligence; 200K, Sheth, Mackay

● Medical Information Decision Assistance and Support; 25K, Prasad, Sheth

● Westwood Partnership to Prevent Juvenile Repeat Violent Offenders; $200K, Sheth, Doran,

Dustin

● Semantic Web-based Data Exchange and Interoperability for OEM-Supplier Collaboration;

89K, Prasad, Sheth

● NIDA National Early Warning System Network (iN3): An Innovative Approach; 299K,

Carlson, Sheth, Boyer, Daniulaityte, Nahas

● SemMat: Federated Semantic Services Platform for Materials Science and Engineering;

315K, Sheth, Prasad, Srinivasan

● Materials Database Knowledge Discovery and Data Mining; 190K, Sheth, Prasad, Srinivasan

Unfunded projects:

● Formal RDF graph model-singleton property with applications to provenance, access control;

massively scalable graph querying and storage (PNNL, NLM, IIT-D, W3C, ….).

● Gender-Based Violence (United Nations Population Fund).

Let’s Talk Big & Smart Data @ Kno.e.sis

• Social Media Big Data - Twitris, eDrugTrends

• Sensor/IoT Big Data - CityPulse, kHealth

• Healthcare Big Data - EMR, Prediction

• Biomedical Big Data - SCOONER, Biomarkers from NextGen

Sequence and Proteomics Data

• Big and Smart Data Science Certificate

Kno.e.sis private cloud:

864 cores,18TB RAM, 17TB SSD, 435TB disk

We are World Class….(last available data, but not updated recently by MAS)

Economic & IP Development

Created Twitris, a Commercial Grade software, which had significant NSF

and AFRL research funds, followed by NSF I-CORP and NSF-PFI-AIR

funding; currently VC/entrepreneurs are evaluating for potential

licensing/start up

One recent patent awarded, two filed

Many more patents filed by companies where Kno.e.sis students intern

ezDI has funded Sponsored Research for the fifth year in the row and now

has major successful products

A local entrepreneur has just signed Sponsored Research that is essentially

incubating his company in Kno.e.sis

On going SBIR/STTR collaborations helping economic development

Extensive Major Media Coverage

Major media coverage

Examples of Real-world Impact

Natural Disaster/Crisis Response Coordination:

During Hurricane Phallin, Uttarakhand floods, JK floods our

technology was used by digital volunteers for real-time

rescue response coordination, saving lives.

Semantic Web-empowered NLU* of clinical text:

commercialized as part of Computer Assisted Coding, etc.

Application deployed for operational use, open source

ontologies, tools, data, patents, etc.

*Natural Language Understanding

Our Most Important Metric of Success

World-class graduates:

• Innovative, confident, good communicators

• Sound technological & engineering skills

• Well-networked, exceptionally well cited

• Granted top internships and awards, hired to top jobs in their fields, able

to pursue careers of their choosing (academic, industry research, R&D,

entrepreneurship, etc.)

• Exceptionally successful and leaders in their area in a short time

See: http://knoesis.org/amit/students

Even more @

http://knoesis.org

http://knoesis.org/amit

Kno.e.sis:

Ohio Center of Excellence in Knowledge-enabled Computing